Biomechatronics in Medical Rehabilitation (eBook)

At the University of Auckland we have 15 years of experience working in biomechatronics and rehabilitation engineering. This experience is in the development and testing of robotics for rehabilitation. Biomechatronic devices we have developed include, upper and lower limb, ankle, hand, finger, wrist as well as EEG and EMG interfaces. This has led to more than 160 journal papers and conference papers.

Preface 5
Acknowledgements 9
Contents 10
Nomenclature 14
1 Introduction 18
1.1 Medical Background and Requirements 18
1.2 BCI Systems 21
1.3 EMG-Based Neuromuscular Interface 26
1.4 Human-Robot Interaction Control 30
1.5 Summary 33
References 33
2 State of the Art 37
2.1 EEG-Based BCI and Its Challenges 38
2.1.1 Steady State Visual Evoked Potentials 38
2.1.2 EEG Signal Processing: Improving the SNR 41
2.1.3 EEG Signal Processing: Signal Translation and Classification 43
2.1.4 Current Limitations 47
2.2 EMG and the Neuromuscular Interface 49
2.2.1 Applications of sEMG 49
2.2.2 sEMG-Based Neuromuscular Interface 52
2.2.3 Current Challenges 53
2.3 Neuromusculoskeletal Models for Gait Rehabilitation 55
2.3.1 Musculoskeletal Model 55
2.3.2 EMG-Driven Models 57
2.4 Discussion 60
2.5 Summary 62
References 62
3 Signal Processing Methods for SSVEP-Based BCIs 69
3.1 Introduction 70
3.2 Adjacent Narrow Band Filter (ANBF) Algorithm 73
3.2.1 Artefact Reduction 73
3.2.2 Frequency Recognition Strategy 74
3.3 Methods and Materials 75
3.3.1 Experimental Protocol 75
3.3.2 EEG Recording and Evaluation 76
3.4 Results 78
3.5 Discussion 82
3.6 Summary 83
References 84
4 SSVEP-Based BCI for Lower Limb Rehabilitation 87
4.1 Introduction 88
4.2 Methods and Materials 89
4.2.1 Subjects and Visual Stimulator 89
4.2.2 SSVEP Signal Processing 90
4.2.3 Robotic Exoskeleton Device 92
4.2.4 Experimental Protocols 92
4.2.5 Control Algorithm 97
4.3 Results 99
4.4 Discussion 101
4.5 Summary 102
References 103
5 A Hybrid BCI for Gaming 106
5.1 Introduction 107
5.2 BCI Setup 108
5.2.1 Signal Recording and Processing 109
5.2.2 Super Street Fighter Video Game 114
5.3 Experimental Method and Results 115
5.3.1 Experimental Protocol 115
5.3.2 Results 116
5.4 Discussion 117
5.5 Summary 119
References 119
6 EMG-Driven Physiological Model for Upper Limb 121
6.1 Neuromusculoskeletal Model 122
6.1.1 Musculoskeletal Geometry Model 122
6.1.2 Musculotendon Model 126
6.1.3 Kinematic Model 128
6.2 Model Sensitivity Analysis 129
6.2.1 Model Parameters 129
6.2.2 Sensitivity Analysis 130
6.2.3 Results and Discussion 132
6.3 Elbow Physiological Model Validation 134
6.3.1 Experimental Setup 134
6.3.2 Model Validation 137
6.4 Summary 141
References 141
7 Exoskeleton Control Based on Neural Interface 143
7.1 Exoskeleton Development 143
7.2 Exoskeleton Control 148
7.2.1 Control System Design 148
7.2.2 Control of the Elbow Joint 150
7.3 Human-Robot Interface 152
7.3.1 Interface Design and Parameter Tuning 152
7.3.2 Graphical User Interface 154
7.4 Summary 157
References 160
8 Muscle Force Estimation Model for Gait Rehabilitation 161
8.1 Patient-Specific Muscle Force Estimation 161
8.1.1 Patient-Specific Musculoskeletal Model 162
8.1.2 Inverse Dynamic Modelling 163
8.1.3 Static Optimisation 164
8.2 PMFE Evaluation and Results 166
8.2.1 PMFE Evaluation 166
8.2.2 Simulation Results 167
8.2.3 Discussion 168
8.3 Human-Inspired Robotic Exoskeleton 171
8.4 Biological Command Based Controller 172
8.4.1 Dynamic Modelling 172
8.4.2 Patient-Specific Muscle Force Estimation 173
8.4.3 PMFE Based Feedforward Controller 174
8.5 PSBc Evaluation and Results 176
8.5.1 Computer Simulation and Results 176
8.5.2 Robot Experiments and Results 178
8.5.3 Discussion 179
8.6 Summary 183
References 183
9 Neuromuscular Model for Gait Rehabilitation 185
9.1 Patient-Specific EMG-Driven Neuromuscular Model 185
9.1.1 The Patient-Specific Musculoskeletal Model 187
9.1.2 Muscle Kinematics 188
9.1.3 EMG-Torque Modelling 189
9.1.4 Global Optimisation Based on Simulink-M 192
9.2 Sensitivity Analysis and Model Evaluation 192
9.2.1 Sensitivity Analysis of MT Parameters to Joint Torque 193
9.2.2 Model Evaluation of the PENm 194
9.2.3 Discussion 196
9.3 Clinical Evaluation of Neuromuscular Model 197
9.3.1 Experimental Evaluation 197
9.3.2 Experiment Protocol 198
9.3.3 Data Processing 200
9.3.4 Discussion 204
9.4 Summary 205
References 206
10 Conclusions and Future Prospects 208
10.1 Book Contributions 208
10.1.1 Effective Brain Computer Interface 208
10.1.2 EMG-Driven Physiological Model 210
10.1.3 Neuromusculoskeletal Model for Gait 212
10.2 Outlook and Future Prospects 214
10.2.1 Future BCIs 214
10.2.2 Neuromuscular Interfaces 215
10.2.3 Neuromuscular Models 217
10.3 Summary 218
References 218
11 Erratum to: Biomechatronics in Medical Rehabilitation 221
Erratum to:& #6